Comments (1)
As for the very simple case with a single model, I would say there is no need to define a multimodel error, but maybe have a specific inference problem that has the same functions (e.g. noise models), but just works with vectors (no keys, just pure np.arrays). But maybe that's something we can decide later on. Similar with the definitions of the priors (decide later). But I think on the other hand we should also allow the user to define the loglike individually (just as an alternative) by providing the option of easily defining user-specific noise models (I see no reason why this whould not work) or directly the complete loglike. So thumbs up from my point of view.
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Related Issues (20)
- remove python 3.7
- Remove sphinx from requirements HOT 2
- Proper VB scaling HOT 2
- Potential bug in our F formula HOT 6
- Prescribed correlation (in noise model) HOT 28
- Remove Gamma.Noninformative()? HOT 1
- Linearity check HOT 3
- Towards `bayem` HOT 6
- Failing visualization test
- Fancy readme
- Docstrings
- pre-commit hooks
- Check ARD implementation HOT 1
- VB `state` variable HOT 1
- VB_postprocess_per_iteration HOT 4
- VB_handle_diverging_ME HOT 4
- Sub-optimal control flow HOT 1
- Visualization of marginalized posteriors HOT 3
- Changes in visualization somehow break the CI HOT 1
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